Search for Single Top Quark Production at DZero Using Neural Networks

TL;DR

This paper reports a search for single top quark production at the Fermilab Tevatron using neural networks to distinguish signals from backgrounds, setting upper limits on production cross sections.

Contribution

It introduces the use of neural networks for separating single top quark signals from backgrounds in collider data.

Findings

Upper limit of 17 pb for s-channel production

Upper limit of 22 pb for t-channel production

Neural networks effectively discriminate signal from background

Abstract

We present a search for electroweak production of single top quarks in ~90 pb^-1 of data collected with the DZero detector at the Fermilab Tevatron collider. Using arrays of neural networks to separate signals from backgrounds, we set upper limits on the cross sections of 17 pb for the s-channel process ppbar->tb+X, and 22 pb for the t-channel process ppbar->tqb+X, both at the 95% confidence level.